SegGPT Meets Co-Saliency Scene

• URL: http://arxiv.org/abs/2305.04396v1
• Date: Mon, 8 May 2023 00:19:05 GMT
• Title: SegGPT Meets Co-Saliency Scene
• Authors: Yi Liu, Shoukun Xu, Dingwen Zhang, Jungong Han
• Abstract summary: We first design a framework to enable SegGPT for the problem of co-salient object detection. Proceed to the next step, we evaluate the performance of SegGPT on the problem of co-salient object detection on three available datasets. We achieve a finding that co-saliency scenes challenges SegGPT due to context discrepancy within a group of co-saliency images.
• Score: 88.53031109255595
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Co-salient object detection targets at detecting co-existed salient objects among a group of images. Recently, a generalist model for segmenting everything in context, called SegGPT, is gaining public attention. In view of its breakthrough for segmentation, we can hardly wait to probe into its contribution to the task of co-salient object detection. In this report, we first design a framework to enable SegGPT for the problem of co-salient object detection. Proceed to the next step, we evaluate the performance of SegGPT on the problem of co-salient object detection on three available datasets. We achieve a finding that co-saliency scenes challenges SegGPT due to context discrepancy within a group of co-saliency images.

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